Systems Administrator

My first move is always to confirm scope and impact before touching anything: is this one service or something wider, and how many users are affected. I post a short status update in our incident channel within the first five minutes, even if it just says we are investigating, because silence is worse than an honest 'we don't know yet'. Once I have a working theory I look for the fastest safe mitigation, often a rollback or a service restart, rather than the fastest permanent fix. At my last role a database connection pool exhausted during a marketing campaign spike; I scaled the pool and restarted the affected service to restore access within eleven minutes, then spent the rest of the day root-causing the actual limit that needed raising. After the incident I write it up: timeline, impact, root cause, and the specific change that prevents a repeat, and I share it with the team, not just my manager.

I treat patching as a scheduled, risk-graded process rather than something reactive. Critical security patches, especially ones tied to an active CVE, get tested in a staging environment and pushed within 48 to 72 hours through an expedited change window. Routine patches follow a monthly cadence: I test them on a small pilot group of non-critical machines first, watch for a few days, then roll out to the rest of the fleet in batches. Every patch window has a documented rollback plan before I start, not something I work out mid-incident. I also keep an inventory of what is running where, because you cannot patch what you have not catalogued: a spreadsheet is not good enough at scale, so I have used tools like WSUS and Ansible to track and automate rollout. The one thing I am strict about is never disabling a patch policy to unblock a deadline; that debt always comes back at a worse time.

I run maintenance work through a ticketing system with agreed SLAs, so it does not get silently deprioritised every time someone pings me directly. I block out recurring time each week for planned work like patching, capacity reviews, and cleanup, and I protect that time the same way I would protect a meeting. When an urgent request comes in, I triage it against actual business impact rather than urgency as the requester perceives it: a broken printer is not the same as a payroll system down. If a request genuinely needs to jump the queue, I say so openly and reschedule the maintenance rather than quietly dropping it, and I flag to my manager when urgent requests are consistently crowding out the planned work, because that is usually a staffing or process signal, not something to just absorb.

I write documentation as I build or change something, not as a task I get to later, because the details are freshest at that point and 'later' rarely happens. My standard is that someone with general admin knowledge but no history with this specific system should be able to follow the doc during an outage at 2am. That means clear diagrams of how services connect, exact commands rather than vague descriptions, and a 'known issues' section for the quirks that are not obvious from the architecture. I keep documentation in a shared wiki rather than local notes, and I review it every time I touch the related system so it does not go stale. On one team I inherited a set of scripts with zero documentation; I spent two weeks reverse engineering and writing them up properly before I would let anyone else rely on them, because undocumented automation is a single point of failure with my name on it.

Every Monday I was manually checking disk space, service status, and certificate expiry across about 40 servers, which took roughly two hours and was exactly the kind of task where a slip meant something got missed. I wrote a PowerShell script that pulled the key metrics from each server, flagged anything outside threshold in red, and emailed a summary report automatically at 6am before I even logged in. It took about a week to build and test properly, including handling servers that were offline or unreachable without the whole script failing. Beyond saving the two hours a week, it caught a certificate that was five days from expiry that I would likely have missed in a manual pass during a busy week. I later extended it to post alerts into our Teams channel in real time instead of waiting for the weekly report, which caught a disk space issue three days before it would have caused an outage.

I noticed our backup job success rate had quietly dropped from 100% to about 92% over a few weeks, with no alerts firing because the monitoring only flagged a job as failed, not a job that succeeded with warnings. I dug into the logs and found a storage volume was approaching capacity, which was causing intermittent truncated backups on three servers. If I had not caught it, we would have discovered the problem the day we actually needed to restore something, which is the worst possible time. I expanded the volume, fixed the affected backup jobs, and then rebuilt the alerting so it treated 'completed with warnings' as a flagged state, not a silent pass. I also set a recurring calendar reminder to spot-check a random backup restore every month, because a backup you have never tested to restore is not really a backup.

We had a recurring issue with our firewall dropping VPN connections under load, and after two rounds of our own troubleshooting we opened a case with the vendor's support. I made sure to hand them a clean, specific problem: exact timestamps, the config version, packet captures from the affected window, and what we had already ruled out, because vague tickets get vague first-line responses and waste days. Their initial fix did not resolve it, so I pushed to get escalated to a senior engineer, backing that request with the data showing the pattern was consistent and reproducible, not a one-off. It turned out to be a known bug in a specific firmware version. I applied the fix they provided in a maintenance window, tested it under a simulated load first, and then documented the whole exchange in our internal wiki so the next person does not have to relitigate the case history if it recurs.

My core stack is a mix of Linux and Windows Server administration, since most environments I have worked in are hybrid. On the Windows side I manage Active Directory, Group Policy, and use PowerShell for anything repetitive. On Linux I am comfortable with the standard shell tools, cron, and configuration management through Ansible rather than making changes by hand on individual boxes, because manual changes do not scale and are hard to audit. For monitoring I have used Nagios and Datadog: Nagios for straightforward up/down and threshold alerting on infrastructure I fully control, Datadog when I need better dashboards and integration with cloud services. I also work with virtualization through VMware and, more recently, containerized workloads, which changes some of the assumptions around patching and lifecycle since the host and the application layer are managed differently. I pick the tool based on what the environment actually needs rather than defaulting to what I know best.

I start from the business side: what is the acceptable recovery time and recovery point for each system, because that determines the backup strategy, not the other way around. A file server with a 24-hour RPO needs a different approach than a transactional database that can only tolerate minutes of data loss. I run a mix of full and incremental backups depending on the system, store copies offsite or in a separate cloud region so a single site failure does not take out both the production system and its backup, and encrypt anything containing sensitive data. The part most teams skip is testing restores: I schedule quarterly restore drills where we actually bring a backup back up in an isolated environment and verify it works end to end, not just that the backup job reported success. That practice caught a corrupted backup chain on one system six months before we would have needed it for a real recovery.

I follow least privilege as the default: users and service accounts get access to exactly what their role requires, nothing broader for convenience. New access requests go through a documented approval process with a named approver, not an informal Slack message, so there is an audit trail. I run access reviews on a quarterly basis, particularly for anything with elevated or administrative rights, and I remove access immediately as part of the offboarding checklist rather than batching it, since a lingering account from someone who left three weeks ago is exactly the kind of gap that gets exploited. For shared or service accounts I avoid static passwords where possible in favour of managed credentials or short-lived tokens. I also keep a clear separation between my day-to-day account and my administrative account, using the admin one only when I am actually doing admin work, so a compromised everyday account does not automatically mean domain admin access.